Evaluation of ChatGPT-Generated Differential Diagnosis for Common Diseases With Atypical Presentation: Descriptive Research.

Background: The persistence of diagnostic errors, despite advances in medical knowledge and diagnostics, highlights the importance of understanding atypical disease presentations and their contribution to mortality and morbidity. Artificial intelligence (AI), particularly generative pre-trained transformers like GPT-4, holds promise for improving diagnostic accuracy, but requires further exploration in handling atypical presentations. Objective: This study aimed to assess the diagnostic accuracy of ChatGPT in generating differential diagnoses for atypical presentations of common diseases, with a focus on the model's reliance on patient history during the diagnostic process. Methods: We used 25 clinical vignettes from the Journal of Generalist Medicine characterizing atypical manifestations of common diseases. Two general medicine physicians categorized the cases based on atypicality. ChatGPT was then used to generate differential diagnoses based on the clinical information provided. The concordance between AI-generated and final diagnoses was measured, with a focus on the top-ranked disease (top 1) and the top 5 differential diagnoses (top 5). Results: ChatGPT's diagnostic accuracy decreased with an increase in atypical presentation. For category 1 (C1) cases, the concordance rates were 17% (n=1) for the top 1 and 67% (n=4) for the top 5. Categories 3 (C3) and 4 (C4) showed a 0% concordance for top 1 and markedly lower rates for the top 5, indicating difficulties in handling highly atypical cases. The χ2 test revealed no significant difference in the top 1 differential diagnosis accuracy between less atypical (C1+C2) and more atypical (C3+C4) groups (χ²1=2.07; n=25; P=.13). However, a significant difference was found in the top 5 analyses, with less atypical cases showing higher accuracy (χ²1=4.01; n=25; P=.048). Conclusions: ChatGPT-4 demonstrates potential as an auxiliary tool for diagnosing typical and mildly atypical presentations of common diseases. However, its performance declines with greater atypicality. The study findings underscore the need for AI systems to encompass a broader range of linguistic capabilities, cultural understanding, and diverse clinical scenarios to improve diagnostic utility in real-world settings.

Hospital Use of a Web-Based Clinical Knowledge Support System and In-Training Examination Performance Among Postgraduate Resident Physicians in Japan: Nationwide Observational Study.

Background: The relationship between educational outcomes and the use of web-based clinical knowledge support systems in teaching hospitals remains unknown in Japan. A previous study on this topic could have been affected by recall bias because of the use of a self-reported questionnaire. Objective: We aimed to explore the relationship between the use of the Wolters Kluwer UpToDate clinical knowledge support system in teaching hospitals and residents' General Medicine In-Training Examination (GM-ITE) scores. In this study, we objectively evaluated the relationship between the total number of UpToDate hospital use logs and the GM-ITE scores. Methods: This nationwide cross-sectional study included postgraduate year-1 and -2 residents who had taken the examination in the 2020 academic year. Hospital-level information was obtained from published web pages, and UpToDate hospital use logs were provided by Wolters Kluwer. We evaluated the relationship between the total number of UpToDate hospital use logs and residents' GM-ITE scores. We analyzed 215 teaching hospitals with at least 5 GM-ITE examinees and hospital use logs from 2017 to 2019. Results: The study population consisted of 3013 residents from 215 teaching hospitals with at least 5 GM-ITE examinees and web-based resource use log data from 2017 to 2019. High-use hospital residents had significantly higher GM-ITE scores than low-use hospital residents (mean 26.9, SD 2.0 vs mean 26.2, SD 2.3; P=.009; Cohen d=0.35, 95% CI 0.08-0.62). The GM-ITE scores were significantly correlated with the total number of hospital use logs (Pearson r=0.28; P<.001). The multilevel analysis revealed a positive association between the total number of logs divided by the number of hospital physicians and the GM-ITE scores (estimated coefficient=0.36, 95% CI 0.14-0.59; P=.001). Conclusions: The findings suggest that the development of residents' clinical reasoning abilities through UpToDate is associated with high GM-ITE scores. Thus, higher use of UpToDate may lead physicians and residents in high-use hospitals to increase the implementation of evidence-based medicine, leading to high educational outcomes.

Effect of a workplace-based learning program on clerkship students' behaviors and attitudes toward evidence-based medicine practice.

In clinical clerkship (CC), medical students can practice evidence-based medicine (EBM) with their assigned patients. Although CC can be a valuable opportunity for EBM education, the impact of EBM training, including long-term behavioral changes, remains unclear. One hundred and nine fourth- and fifth-year medical students undergoing CC at a medical school in Japan attended a workplace-based learning program for EBM during CC (WB-EBM), which included the practice of the five steps of EBM. The program's effect on the students' attitudes toward EBM in CC was assessed through questionnaires. A total of 88 medical students participated in the program. Responses to the questionnaire indicated high satisfaction with the WB-EBM program. The most common theme in students' clinical problems with their assigned patients was the choice of treatment, followed by its effect. Based on the responses in the post-survey for the long-term effects of the program, the frequency of problem formulation and article reading tended to increase in the 'within six months' group comprising 18 students who participated in the WB-EBM program, compared with the control group comprising 34 students who did not. Additionally, the ability to self-assess problem formulation was significantly higher, compared with the control group. However, among 52 students who participated in the WB-EBM program more than six months later, EBM-related behavioral habits in CC and self-assessments of the five steps of EBM were not significantly different from those in the control group. The WB-EBM program was acceptable for medical students in CC. It motivated them to formulate clinical questions and enhanced their critical thinking. Moreover, the WB-EBM program can improve habits and self-evaluations about EBM. However, as its effects may not last more than six months, it may need to be repeated across departments throughout CC to change behavior in EBM practice.

The Administration of Lemborexant at Admission is Not Associated with Inpatient Falls: A Multicenter Retrospective Observational Study.

Purpose: There has been no large-scale investigation into the association between the use of lemborexant, suvorexant, and ramelteon and falls in a large population. This study, serving as a pilot investigation, was aimed at examining the relationship between inpatient falls and various prescribed hypnotic medications at admission. Patients and Methods: This study was a sub-analysis of a multicenter retrospective observational study conducted over a period of 3 years. The target population comprised patients aged 20 years or above admitted to eight hospitals, including chronic care, acute care, and tertiary hospitals. We extracted data on the types of hypnotic medications prescribed at admission, including lemborexant, suvorexant, ramelteon, benzodiazepines, Z-drugs, and other hypnotics; the occurrence of inpatient falls during the hospital stay; and patients' background information. To determine the outcome of inpatient falls, items with low collinearity were selected and included as covariates in a forced-entry binary logistic regression analysis. Results: Overall, 150,278 patients were included in the analysis, among whom 3,458 experienced falls. The median age of the entire cohort was 70 years, with men constituting 53.1%. Binary logistic regression analysis revealed that the prescription of lemborexant, suvorexant, and ramelteon at admission was not significantly associated with inpatient falls. Conclusion: The administration of lemborexant, suvorexant, and ramelteon at admission may not be associated with inpatient falls.

Importance of Patient History in Artificial Intelligence-Assisted Medical Diagnosis: Comparison Study.

Background: Medical history contributes approximately 80% to a diagnosis, although physical examinations and laboratory investigations increase a physician's confidence in the medical diagnosis. The concept of artificial intelligence (AI) was first proposed more than 70 years ago. Recently, its role in various fields of medicine has grown remarkably. However, no studies have evaluated the importance of patient history in AI-assisted medical diagnosis. Objective: This study explored the contribution of patient history to AI-assisted medical diagnoses and assessed the accuracy of ChatGPT in reaching a clinical diagnosis based on the medical history provided. Methods: Using clinical vignettes of 30 cases identified in The BMJ, we evaluated the accuracy of diagnoses generated by ChatGPT. We compared the diagnoses made by ChatGPT based solely on medical history with the correct diagnoses. We also compared the diagnoses made by ChatGPT after incorporating additional physical examination findings and laboratory data alongside history with the correct diagnoses. Results: ChatGPT accurately diagnosed 76.6% (23/30) of the cases with only the medical history, consistent with previous research targeting physicians. We also found that this rate was 93.3% (28/30) when additional information was included. Conclusions: Although adding additional information improves diagnostic accuracy, patient history remains a significant factor in AI-assisted medical diagnosis. Thus, when using AI in medical diagnosis, it is crucial to include pertinent and correct patient histories for an accurate diagnosis. Our findings emphasize the continued significance of patient history in clinical diagnoses in this age and highlight the need for its integration into AI-assisted medical diagnosis systems.

Distribution of internal medicine rotations among resident physicians in Japan: a nationwide, multicenter, cross-sectional study.

BACKGROUND: In Japan, postgraduate clinical training encompasses a 2-year residency program, including at least 24 weeks of internal medicine (IM) rotations. However, the fragmented structure of these rotations can compromise the training's quality and depth. For example, a resident might spend only a few weeks in cardiology before moving to endocrinology, without sufficient time to deepen their understanding or have clinical experience. This study examined current patterns and lengths of IM rotations within the Japanese postgraduate medical system. It scrutinized the piecemeal approach-whereby residents may engage in multiple short-term stints across various subspecialties without an overarching, integrated experience-and explored potential consequences for their clinical education. METHODS: This nationwide, multicenter, cross-sectional study used data from self-reported questionnaires completed by participants in the 2022 General Medicine In-Training Examination (GM-ITE). Data of 1,393 postgraduate year (PGY) one and two resident physicians who participated in the GM-ITE were included. We examined the IM rotation duration and number of IM subspecialties chosen by resident physicians during a 2-year rotation. RESULTS: Approximately half of the participants chose IM rotation periods of 32-40 weeks. A significant proportion of participants rotated in 5-7 internal medicine departments throughout the observation period. Notable variations in the distribution of rotations were observed, characterized by a common pattern where resident physicians typically spend 4 weeks in each department before moving to the next. This 4-week rotation is incrementally repeated across different subspecialties without a longer, continuous period in any single area. Notably, 39.7% of participants did not undertake general internal medicine rotations. These results suggest a narrowed exposure to medical conditions and patient care practices. CONCLUSIONS: Our study highlights the need to address the fragmented structure of IM rotations in Japan. We suggest that short, specialized learning periods may limit the opportunity to gain broad in-depth knowledge and practical experience. To improve the efficacy of postgraduate clinical education, we recommend fostering more sustained and comprehensive learning experiences.

The differential diagnosis of medical and psychogenic disease in primary care.

Diagnosis and management of psychogenic diseases such as conversion disorder, somatic symptom disorder (SSD), illness anxiety disorder, falsehood disorder, and psychotic disorder require an elaborate biopsychosocial approach and are often challenging. Herein, we propose the following points to differentiate medical diseases from these psychogenic diseases: correspondence between symptoms and objective findings or activities of daily living (ADL) impairment; placebo effect; clear provocative or palliative factors; progressive time course; paroxysmal or intermittent symptoms; unfamiliar but not strange expressions; symptoms worsen during sleep or rest.

How Do We Establish the Utility and Evidence of General Medicine in Japan?

Hospital Medicine in the United States has achieved significant progress in the accumulation of evidence. This development has influenced the increasing societal demand for General Medicine in Japan. Generalists in Japan actively engage in a wide range of interdisciplinary clinical practices, education, and management. Furthermore, Generalists have also contributed to advances in research. However, there is limited evidence regarding the benefits of General Medicine in Japan in all these areas, with most of the evidence derived from single-center studies. In Japan, the roles of Generalists are diverse, and the comprehensive definition of General Medicine makes it difficult to clearly delineate its scope. This results in an inadequate accumulation of evidence regarding the benefits of General Medicine, potentially making it less attractive to the public and younger physicians. Therefore, it is necessary to categorize General Medicine and collect clear evidence regarding its benefits.

Validation and Improvement of the Saga Fall Risk Model: A Multicenter Retrospective Observational Study.

Purpose: We conducted a pilot study in an acute care hospital and developed the Saga Fall Risk Model 2 (SFRM2), a fall prediction model comprising eight items: Bedriddenness rank, age, sex, emergency admission, admission to the neurosurgery department, history of falls, independence of eating, and use of hypnotics. The external validation results from the two hospitals showed that the area under the curve (AUC) of SFRM2 may be lower in other facilities. This study aimed to validate the accuracy of SFRM2 using data from eight hospitals, including chronic care hospitals, and adjust the coefficients to improve the accuracy of SFRM2 and validate it. Patients and Methods: This study included all patients aged ≥20 years admitted to eight hospitals, including chronic care, acute care, and tertiary hospitals, from April 1, 2018, to March 31, 2021. In-hospital falls were used as the outcome, and the AUC and shrinkage coefficient of SFRM2 were calculated. Additionally, SFRM2.1, which was modified from the coefficients of SFRM2 using logistic regression with the eight items comprising SFRM2, was developed using two-thirds of the data randomly selected from the entire population, and its accuracy was validated using the remaining one-third portion of the data. Results: Of the 124,521 inpatients analyzed, 2,986 (2.4%) experienced falls during hospitalization. The median age of all inpatients was 71 years, and 53.2% were men. The AUC of SFRM2 was 0.687 (95% confidence interval [CI]:0.678-0.697), and the shrinkage coefficient was 0.996. SFRM2.1 was created using 81,790 patients, and its accuracy was validated using the remaining 42,731 patients. The AUC of SFRM2.1 was 0.745 (95% CI: 0.731-0.758). Conclusion: SFRM2 showed good accuracy in predicting falls even on validating in diverse populations with significantly different backgrounds. Furthermore, the accuracy can be improved by adjusting the coefficients while keeping the model's parameters fixed.

Development of a Clinical Simulation Video to Evaluate Multiple Domains of Clinical Competence: Cross-Sectional Study.

BACKGROUND: Medical students in Japan undergo a 2-year postgraduate residency program to acquire clinical knowledge and general medical skills. The General Medicine In-Training Examination (GM-ITE) assesses postgraduate residents' clinical knowledge. A clinical simulation video (CSV) may assess learners' interpersonal abilities. OBJECTIVE: This study aimed to evaluate the relationship between GM-ITE scores and resident physicians' diagnostic skills by having them watch a CSV and to explore resident physicians' perceptions of the CSV's realism, educational value, and impact on their motivation to learn. METHODS: The participants included 56 postgraduate medical residents who took the GM-ITE between January 21 and January 28, 2021; watched the CSV; and then provided a diagnosis. The CSV and GM-ITE scores were compared, and the validity of the simulations was examined using discrimination indices, wherein ≥0.20 indicated high discriminatory power and >0.40 indicated a very good measure of the subject's qualifications. Additionally, we administered an anonymous questionnaire to ascertain participants' views on the realism and educational value of the CSV and its impact on their motivation to learn. RESULTS: Of the 56 participants, 6 (11%) provided the correct diagnosis, and all were from the second postgraduate year. All domains indicated high discriminatory power. The (anonymous) follow-up responses indicated that the CSV format was more suitable than the conventional GM-ITE for assessing clinical competence. The anonymous survey revealed that 12 (52%) participants found the CSV format more suitable than the GM-ITE for assessing clinical competence, 18 (78%) affirmed the realism of the video simulation, and 17 (74%) indicated that the experience increased their motivation to learn. CONCLUSIONS: The findings indicated that CSV modules simulating real-world clinical examinations were successful in assessing examinees' clinical competence across multiple domains. The study demonstrated that the CSV not only augmented the assessment of diagnostic skills but also positively impacted learners' motivation, suggesting a multifaceted role for simulation in medical education.

Association of sleep quality with duty hours, mental health, and medical errors among Japanese postgraduate residents: a cross-sectional study.

Long duty hours (DH) impair sleep and negatively affect residents' health and medical safety. This cross-sectional study investigated the association among residents' DH, sleep duration, insomnia, sleep impairment, depressive symptoms, and self-reported medical errors among 5579 residents in Japan who completed the General Medicine In-Training Examination (2021) and participated in the training-environment survey. Weekly DH was classified under seven categories. Sleep duration and insomnia symptoms, from the Athens Insomnia Scale, were analysed to determine sleep impairment; depressive symptoms and medical errors were self-reported. Among 5095 residents, 15.5% slept < 5 h/day, and 26.7% had insomnia. In multivariable analysis, compared with ≥ 60 and < 70, DH ≥ 90 h/week associated with shorter sleep duration and worsen insomnia symptoms. Shorter durations of sleep and more intense symptoms of insomnia were associated with increased depressive symptoms. Medical errors increased only among residents with insomnia, but were not associated with sleep duration. DH > 90 h/week could lead to shorter sleep duration, worsen insomnia symptoms, and negatively impact well-being and medical safety. There was no significant association between sleep duration and medical errors; however, insomnia conferred an increased risk of medical errors. Limiting DH for residents to avoid excessive workload can help improve resident sleep, enhance resident well-being, and potentially reduce insomnia-associated medical errors.

Educational strategies related to information science and technology for medical students: General medicine physicians' perspective.

The Model Core Curriculum for Medical Education in Japan was revised in 2022. It aimed to reflect changes in the nature of medical care, including the advancement of medical technology through the use of information science and technology and artificial intelligence in the Society 5.0 era. We summarize recommendations for good practice regarding learning strategies from the perspective of general medicine.

Three Subtypes of Cutaneous Nerve Entrapment Syndrome: A Narrative Review.

Anterior, lateral, and posterior cutaneous nerve entrapment syndromes have been proposed as etiologies of trunk pain. However, while these syndromes are analogous, comprehensive reports contrasting the three subtypes are lacking. We therefore reviewed the literature on anterior, lateral, and posterior cutaneous nerve entrapment syndrome. We searched the PubMed and Cochrane Library databases twice for relevant articles published between March and September 2022. In addition to 16 letters, technical reports, and review articles, a further 62, 6, and 3 articles concerning anterior, lateral, and posterior cutaneous nerve entrapment syndromes, respectively, were included. These syndromes are usually diagnosed based solely on unique history and examination findings; however, the diagnostic process may be prolonged, and multiple re-evaluations are required. The most common first-line treatment is trigger point injection; however, the management of refractory cases remains unclear. Awareness of this disease should be expanded to medical departments other than general medicine.

Mediastinal hematoma due to traumatic injury to the azygous vein.

Rupture of the azygous vein may result from abrupt deceleration applied to the mobile azygous arch, which can initiate shearing forces within the thorax.

Developing Medical Education Curriculum Reform Strategies to Address the Impact of Generative AI: Qualitative Study.

BACKGROUND: Generative artificial intelligence (GAI), represented by large language models, have the potential to transform health care and medical education. In particular, GAI's impact on higher education has the potential to change students' learning experience as well as faculty's teaching. However, concerns have been raised about ethical consideration and decreased reliability of the existing examinations. Furthermore, in medical education, curriculum reform is required to adapt to the revolutionary changes brought about by the integration of GAI into medical practice and research. OBJECTIVE: This study analyzes the impact of GAI on medical education curricula and explores strategies for adaptation. METHODS: The study was conducted in the context of faculty development at a medical school in Japan. A workshop involving faculty and students was organized, and participants were divided into groups to address two research questions: (1) How does GAI affect undergraduate medical education curricula? and (2) How should medical school curricula be reformed to address the impact of GAI? The strength, weakness, opportunity, and threat (SWOT) framework was used, and cross-SWOT matrix analysis was used to devise strategies. Further, 4 researchers conducted content analysis on the data generated during the workshop discussions. RESULTS: The data were collected from 8 groups comprising 55 participants. Further, 5 themes about the impact of GAI on medical education curricula emerged: improvement of teaching and learning, improved access to information, inhibition of existing learning processes, problems in GAI, and changes in physicians' professionality. Positive impacts included enhanced teaching and learning efficiency and improved access to information, whereas negative impacts included concerns about reduced independent thinking and the adaptability of existing assessment methods. Further, GAI was perceived to change the nature of physicians' expertise. Three themes emerged from the cross-SWOT analysis for curriculum reform: (1) learning about GAI, (2) learning with GAI, and (3) learning aside from GAI. Participants recommended incorporating GAI literacy, ethical considerations, and compliance into the curriculum. Learning with GAI involved improving learning efficiency, supporting information gathering and dissemination, and facilitating patient involvement. Learning aside from GAI emphasized maintaining GAI-free learning processes, fostering higher cognitive domains of learning, and introducing more communication exercises. CONCLUSIONS: This study highlights the profound impact of GAI on medical education curricula and provides insights into curriculum reform strategies. Participants recognized the need for GAI literacy, ethical education, and adaptive learning. Further, GAI was recognized as a tool that can enhance efficiency and involve patients in education. The study also suggests that medical education should focus on competencies that GAI hardly replaces, such as clinical experience and communication. Notably, involving both faculty and students in curriculum reform discussions fosters a sense of ownership and ensures broader perspectives are encompassed.

Cancer Screening Abstinence Rates and Rationales Among Regular Outpatients at a Rural Hospital in Japan: A Cross-Sectional Study.

Purpose: This study aimed to investigate cancer screening rates and the reasons for not undergoing screening among patients who regularly visited the Sanmu Medical Center. Patients and Methods: This prospective observational study recruited patients aged ≥40 years with regular clinic visits to Sanmu Medical Center during October 2019. We conducted a self-administered survey to determine the patient's sex and whether they underwent cancer screening in 2019, and if not, the reason for the same. The primary outcome measure was the percentage of people who did not undergo cancer screening. Results: A total of 198 responses (108 male respondents) were obtained. Among them, 189 were valid responses (valid response rate 94.5%). One hundred and twenty-nine patients (68.2%, 76 male) had not undergone screening. The most common reasons provided were "I have regular regular clinic visits and do not think they are necessary" (N = 65, 50.3%), "I underwent a gastroscopy within 2 years, a colorectal camera examination within a few years, and a chest radiography within a year" (42.5%), and "I have a separate complete medical checkup" (N = 15, 11.6%). Of the 65 patients who responded that their cancer screenings were unnecessary, 42 patients (64.6%) had not undergone a gastroscopy within 2 years, a colorectal camera examination within a few years, or a chest radiography or examination within a year. Conclusion: Roughly half of the respondents who did not undergo cancer screening elected to abstain because they believed that regular hospital visits were sufficient. Encouraging patients who regularly visit medical institutions to receive cancer screening is therefore necessary.

Protecting the primary care physicians' well-being.

Seminar participants collaborated as a team to improve their organization, work environment, and labor issues using the Plan-Do-Check-Act (PDCA) cycle. The PDCA cycle helps healthcare providers identify risks and hazards in their work environment and address daily issues. It guides them in planning and executing improvements while enabling progress tracking and encouraging further considerations for implementation.

The influence of Gamification on medical students' diagnostic decision making and awareness of medical cost: a mixed-method study.

BACKGROUND: The gamification of learning increases student enjoyment, and motivation and engagement in learning tasks. This study investigated the effects of gamification using decision-making cards (DMCs) on diagnostic decision-making and cost using case scenarios. METHOD: Thirty medical students in clinical clerkship participated and were randomly assigned to 14 small groups of 2-3 medical students each. Decision-making was gamified using DMCs with a clinical information heading and medical cost on the front, and clinical information details on the back. First, each team was provided with brief clinical information on case scenarios. Subsequently, DMCs depending on the case were distributed to each team, and team members chose cards one at a time until they reached a diagnosis of the case. The total medical cost was then scored based on the number and contents of cards drawn. Four case scenarios were conducted. The quantitative outcomes including confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical costs were measured before and after our gamification by self-evaluation using a 7-point Likert scale. The qualitative component consisted of a content analysis on the benefits of learning clinical reasoning using DMCs. RESULT: Confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical cost were significantly higher after the gamification. Furthermore, comparing the clinical case scenario tackled last with the one tackled first, the average medical cost of all cards drawn by students decreased significantly from 11,921 to 8,895 Japanese yen. In the content analysis, seven advantage categories of DMCs corresponding to clinical reasoning components were extracted (information gathering, hypothesis generation, problem representation, differential diagnosis, leading or working diagnosis, diagnostic justification, and management and treatment). CONCLUSION: Teaching medical students clinical reasoning using DMCs can improve clinical decision-making confidence and learning motivation, and reduces medical cost in clinical case scenarios. In addition, it can help students to acquire practical knowledge, deepens their understanding of clinical reasoning, and identifies several important clinical reasoning skills including diagnostic decision-making and awareness of medical costs. Gamification using DMCs can be an effective teaching method for improving medical students' diagnostic decision-making and reducing costs.